estimatePortRisk

Estimate portfolio risk according to risk proxy associated with corresponding object

Syntax

prsk = estimatePortRisk(obj,pwgt)

Description

prsk = estimatePortRisk(obj,pwgt) estimates portfolio risk according to the risk proxy associated with the corresponding object (obj) for Portfolio, PortfolioCVaR, or PortfolioMAD objects. For details on the respective workflows when using these different objects, see Portfolio Object Workflow, PortfolioCVaR Object Workflow, and PortfolioMAD Object Workflow.

Examples

Standard Deviation of Portfolio Returns as the Proxy for Portfolio Risk for a Portfolio Object

Given portfolio p, use the estimatePortRisk function to show the standard deviation of portfolio returns for each portfolio in pwgt.

m = [ 0.05; 0.1; 0.12; 0.18 ];
C = [ 0.0064 0.00408 0.00192 0; 
      0.00408 0.0289 0.0204 0.0119;
      0.00192 0.0204 0.0576 0.0336;
      0 0.0119 0.0336 0.1225 ];
 
p = Portfolio;
p = setAssetMoments(p, m, C);
p = setDefaultConstraints(p);
pwgt = estimateFrontierLimits(p);
prsk = estimatePortRisk(p, pwgt);
disp(prsk)

    0.0769
    0.3500

Conditional Value-at-Risk of Portfolio Returns as the Proxy for Portfolio Risk for a PortfolioCVaR Object

Given a portfolio pwgt, use the estimatePortRisk function to show the conditional value-at-risk (CVaR) of portfolio returns for each portfolio.

m = [ 0.05; 0.1; 0.12; 0.18 ];
C = [ 0.0064 0.00408 0.00192 0; 
    0.00408 0.0289 0.0204 0.0119;
    0.00192 0.0204 0.0576 0.0336;
    0 0.0119 0.0336 0.1225 ];
m = m/12;
C = C/12;

rng(11);

AssetScenarios = mvnrnd(m, C, 20000);

p = PortfolioCVaR;
p = setScenarios(p, AssetScenarios);
p = setDefaultConstraints(p);
p = setProbabilityLevel(p, 0.95);

pwgt = estimateFrontierLimits(p);
prsk = estimatePortRisk(p, pwgt);
disp(prsk)

    0.0407
    0.1911

The function rng($$seed$$) resets the random number generator to produce the documented results. It is not necessary to reset the random number generator to simulate scenarios.

Mean-Absolute Deviation Returns as the Proxy for Portfolio Risk for a PortfolioMAD Object

Given a portfolio pwgt, use the estimatePortRisk function to show the mean-absolute deviation of portfolio returns for each portfolio.

m = [ 0.05; 0.1; 0.12; 0.18 ];
C = [ 0.0064 0.00408 0.00192 0; 
    0.00408 0.0289 0.0204 0.0119;
    0.00192 0.0204 0.0576 0.0336;
    0 0.0119 0.0336 0.1225 ];
m = m/12;
C = C/12;

rng(11);

AssetScenarios = mvnrnd(m, C, 20000);

p = PortfolioMAD;
p = setScenarios(p, AssetScenarios);
p = setDefaultConstraints(p);


pwgt = estimateFrontierLimits(p);
prsk = estimatePortRisk(p, pwgt);
disp(prsk)

    0.0177
    0.0809

The function rng($$seed$$) resets the random number generator to produce the documented results. It is not necessary to reset the random number generator to simulate scenarios.

Input Arguments

obj — Object for portfolio

object

Object for portfolio, specified using Portfolio, PortfolioCVaR, or PortfolioMAD object. For more information on creating a portfolio object, see

• Portfolio

• PortfolioCVaR

• PortfolioMAD

Data Types: object

pwgt — Collection of portfolios

matrix

Collection of portfolios, specified as a NumAssets-by-NumPorts matrix, where NumAssets is the number of assets in the universe and NumPorts is the number of portfolios in the collection of portfolios.

Data Types: double

Output Arguments

prsk — Estimates for portfolio risk according to the risk proxy associated with the corresponding object (obj) for each portfolio in pwgt

vector

Estimates for portfolio risk according to the risk proxy associated with the corresponding object (obj) for each portfolio in pwgt, returned as a NumPorts vector.

prsk is returned for a Portfolio, PortfolioCVaR, or PortfolioMAD input object (obj).

Tips

You can also use dot notation to estimate portfolio risk according to the risk proxy associated with the corresponding object (obj).

prsk = obj.estimatePortRisk(pwgt);